Distance Matrix Generation for Dynamic Vehicle Routing Optimization in Transport Fleets Management

EasyChair Preprint no. 6801

Abstract

The article focuses on the dynamic update of the distance matrix, one of the key datasets used in the optimization of transport issues. In the case of a dynamically changing list of destinations, a continuous and effective update of the data is required, e.g. from more and more popular services such as Mapping APIs. The time-consuming nature of this process, which may extend the planning process, was emphasized. The article discusses the possibility of generating temporary values of the distance matrix based on the correction of the quasi-Euclidean distance. The impact of update progress on the some optimization algorithms was investigated. The research was carried out on the example of the real VRP problem. The obtained post-optimization results could be compared with the results obtained manually by experienced planners. It was found that the degree of update of the distance matrix influences the cost reduction in a nondeterministic way.

Keyphrases: distance matrix, evolutionary algorithm, greedy algorithm, Mapping API, Optimization, VRP, WFM

@Booklet{EasyChair:6801,
  author = {Radosław Belka and Mateusz Godlewski},
  title = {Distance Matrix Generation for Dynamic Vehicle Routing Optimization in Transport Fleets Management},
  howpublished = {EasyChair Preprint no. 6801},

  year = {EasyChair, 2021}}